OpenAI and Digital Discovery Group

Case Study: Writing a Custom GPT

A black Harley-Davidson motorcycle is parked in front of a chain-link fence, with a sign for APL Performance, multiple palm trees, and parked cars under a clear blue sky.

Case Study: Writing a Custom GPT

Logo for APL Performance Bikes with bold red and white text on a blue background.
A man working on a black Indian motorcycle inside a showroom with various motorcycles lined up.

Moto Manual Assistant (V1.4)

Problem Statement: APL Performance Bikes services hundreds of Indian Motorcycles each year, emphasising performance tuning and rider confidence. Their workshop is the finest in the country, but searching for technical specifications, navigating cumbersome PDFs, and verifying service procedures can be quite time-consuming.

Moto Manual Assistant – AI That Talks Like a Mechanic

The Moto Manual Assistant is designed to provide APL with a powerful, on-demand tool for Indian Motorcycle owners. It offers fast and accurate service information and reduces the time spent searching through manuals or answering repetitive technical questions, helping to save both time and money.

Try the Live Demo

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In Page Demo

This is a preset simulation of a conversation styled like a GPT interaction between a mechanic and MotoManual's AI assistant. It is designed to visually mimic the ChatGPT experience in a static yet realistic format. Instead of utilising a live AI model, it operates using preloaded content.

Click the Show GPT Response to get an idea of how this works. You can also download a PDF of the output in plain, formatted text.

Can you walk me through adjusting the Scout's drive belt?
A man wearing a Harley Davidson motorcycle shirt and headphones rides a motorcycle on a dynamometer in a testing facility.

Risk vs Reward: The Safe Way to Use AI in Your Business

Idea

Built a Moto Manual Assistant — a custom GPT trained on the exact models.

Implementation

The Moto Manual Assistant is currently starting its pilot phase, which involves testing the system's features and functionalities with a select group of users. This phase aims to gather valuable feedback and ensure that the assistant can effectively meet the needs of motorcycle enthusiasts and owners. During this stage, the team will closely monitor its performance, usability, and user satisfaction to make any necessary adjustments before a full-scale launch.

The interface was designed to facilitate concise conversations: users can ask questions, receive answers, and proceed efficiently.

Key integrations included:

  • Indexing OEM service manuals and technical bulletins

  • Custom prompt tuning to align with mechanical terminology

  • Controlled scope to ensure accuracy and reliability

  • Easy mobile access for use in garages and on the roadside

What Makes It Unique?

While many workshops discuss “innovation,” APL has taken it a step further by embracing it. The Moto Manual Assistant is not just a gimmick but a practical tool for customers and mechanics. This reinforces APL’s reputation as a leader in performance and a pioneer in digital service enablement.

FAQs

What exactly is the Moto Manual Assistant?

AI helps automate tasks such as generating reports, organising spreadsheets, summarising meetings, creating content, handling customer queries, and accelerating research, potentially saving significant time across your business.

Is this information public or exclusive to APL customers?

It’s primarily for internal workshop use and APL customers. However, depending on the rollout strategy, it may eventually be opened up more broadly to Indian riders Australia-wide. That’s still being scoped.

Does it replace a mechanic?

Hell no. It assists one. It’s a tool, just like a torque wrench or lift. The difference is, this one talks back and remembers all the specs, service intervals, and quirks without blinking. It's about efficiency and accuracy, not replacement. Does AI really create content?

Is it being used in the workshop

At this moment, we are still in the early stages of evaluating the use and accuracy of the system during the pilot phase. This phase is crucial as it allows us to gather valuable data and insights to ensure the final implementation meets our standards and user needs.

Contact us.

[email protected]

Industry Recommendations

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